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Turo Interview Questions

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Machine Learning

Encoding Categorical Features

Bank Fraud Model

Lasso vs Ridge

Bagging vs Boosting

Type-ahead Search

Data Structures & Algorithms

Given a list of integers, and an integer N, write a function to find all combinations that sum to the value N.

Sum to N

Write code to generate a sample from a multinomial distribution with keys 

Drawing Balls From Bin

Determine whether there exists a permutation of an input string that is a palindrome.

Permutation Palindrome

Weighted Keys

Given an array and a target integer, write a function that returns the indices of two integers in the array that add up to the target integer.

Target Indices

Write a query to select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary.

Employee Salaries

User Experience Percentage

Distance Traveled

Download Facts

Write a query to get the average commute time for each commuter in New York

Average Commute Time

Business Case

Declining Applicants

Game Feature Home

Instant Eat Reintroduction

Delivery Fees

Apartment Pricing

Statistics

Time on FB Distribution

P-value to a Layman

What are the assumptions of linear regression?

Assumptions of Linear Regression

MLE vs MAP

Determine the cause of the drop in capital approval rates.

Approval Drop

When an interviewer asks a question along the lines of:

<ul>
<li>What would your current manager say about you? What constructive criticisms might he give?</li>
<li>What are your three biggest strengths and weaknesses you have identified in yourself?</li>
</ul>

How would you respond?

When asked about your strengths in an interview, what is an effective way to respond?

When asked about your strengths in an interview, what is an effective way to respond?

Your Strengths and Weaknesses I

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Your Strengths and Weaknesses II

What do you tell an interviewer when they ask you what your strengths and weaknesses are?

Your Strengths and Weaknesses

Brainteasers

When an interviewer asks you a question along the lines of:

<ul>
<li>Why did you apply to our company?</li>
<li>What are you looking for in your next job?</li>
<li>What makes you a good fit for our company?</li>
</ul>

How should you respond?

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

Why Do You Want to Work With Us I

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

Why Do You Want to Work With Us II

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

Why Do You Want to Work With Us III

How would you answer when an Interviewer asks why you applied to their company?

Why Do You Want to Work With Us

Describe a data project you worked on. What were some of the challenges you faced?

Describing a data project and its challenges

Hurdles In Data Projects

Analytics

How would you explain what a p-value is to someone who is not technical?

What does a p-value in a statistical test represent?

What does a p-value in a statistical test represent?

P-value to a Layman I

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

P-value to a Layman II

What are the assumptions of linear regression?

Which assumption of the residuals of the standard linear regression model can not be overcome by increasing the sample size?

Regression assumptions

Let’s say that you’re training a classification model.

How would you combat overfitting when building tree-based models?

Let's say that you're training a classification model.   How would you combat overfitting when building tree-based models?

Overfit Avoidance

How would you handle the data preparation for building a machine learning model using imbalanced data?

Addressing imbalanced data in machine learning through carefully prepared techniques.

Data Preparation for Imbalanced Data

Let’s say we’re comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? 

Give an example of the tradeoffs between the two.

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

Bagging vs. Boosting

Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

Given a string, write a function to determine if it is palindrome or not.

Note: A palindrome is a word/string that is read the same way forward as it is backward, e.g. <code>&#39;reviver&#39;</code>, <code>&#39;madam&#39;</code>, <code>&#39;deified&#39;</code> and <code>&#39;civic&#39;</code> are all palindromes, while <code>&#39;tree&#39;</code>, <code>&#39;music&#39;</code> and <code>&#39;person&#39;</code> are not palindromes.

Example:

Input:

<pre tabindex="0" class="chroma"><code>word1 = &#34;tree&#34;
word2 = &#34;radar&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def is_palindrome(word1) -&gt; False
def is_palindrome(word2) -&gt; True
</code></pre>

Given a string, write a function to determine if it is palindrome or not.

String Palindromes

Imagine you are asked to build a machine learning model to decide new loan approvals for a
financial firm. You ask the data department in the company for a subset of data to get started
working on the problem. The data includes different features about applicants such as age,
occupation, zip code, height, number of children, favorite color, etc. You decide to build
multiple machine learning models to test out different ideas before settling on the best one.

How would you explain the bias-variance tradeoff with regards to
building and choosing a model to use?

Bias vs. Variance Tradeoff

Explain the difference between the XGBoost and random forest algorithms and give an example where you would use one over the other.

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

XGBoost vs Random Forest: Choice

Xgboost vs Random Forest

How does random forest generate the forest? Additionally, why would we use it over other algorithms such as logistic regression?

What happens when you average the output on multiple decision trees?

What happens when you average the output on multiple decision trees?

Average Trees

Random Forest Explanation

Let’s say that you work at a B2B SAAS company that’s interested in testing the pricing of different levels of subscriptions.

Your project manager comes to you and asks you to run a two-week-long A/B test to test an increase in pricing.

How would you approach designing this test? How would you determine whether the increase in pricing is a good business decision?

Testing Price Increase

A/B Testing

Tell me about a project in which you had to clean and organize a large dataset.

Describing a real-world data cleaning and organization project

Data Cleaning Experiences

Data Pipelines

What are the key differences between classification models and regression models?

What is the MOST important difference between regression and classification models?

What is the MOST important difference between regression and classification models?

Classification vs Regression

Classification and Regression

Given an array and a target integer, write a function <code>sum_pair_indices</code> that returns the indices of two integers in the array that add up to the target integer. If not found, just return an empty list.

Note: Can you do it on $O(n)$ time?

Note: Even though there could be many solutions, only one needs to be returned.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>array = [1 2 3 4] 
target = 5 
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def sum_pair_indices(array, target) -&gt; [0 3] or [1 2]
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>array = [3]
target = 6 
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>Do NOT return [0 0] as you can&#39;t use an index twice.
</code></pre>

Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

Experiment Validity

Let’s say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service in addition that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

How would we build this model?

Let’s say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

Which statement is true?

Let's say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

Which statement is true?

What’s the difference between Lasso and Ridge Regression?

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

What’s the relationship between PCA and K-means clustering?

What does the variable “k” in k-means clustering refer to?

What does the variable "k" in k-means clustering refer to?

Input of K-means

PCA and K-Means

The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding ones, usually starting with 0 and 1. It is often used in algorithm examples, and is defined by the following formula: F(n) = F(n-1) + F(n-2), with F(0) = 0 and F(1) = 1.

Your task is to implement the Fibonacci algorithm in three different methods:
1. Recursively
2. Iteratively
3. Using Memoization

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>n = 5
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>fibonacci(n) -&gt; 5
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>n = 10
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>fibonacci(n) -&gt; 55
</code></pre>

The Fibonacci sequence starts as follows: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55…

This question requires the implementation of the Fibonacci sequence using three different methods: recursively, iteratively, and using memoization.

Implementing the Fibonacci Sequence in Three Different Methods

You’re given a string that may contain the characters <code>{</code>, <code>}</code>, <code>[</code>, <code>]</code>, <code>(</code>, and <code>)</code>.

Task: Verify that the string is balanced. A balanced string is one where every opening character, <code>{</code>, <code>[</code>, or <code>(</code>, has a corresponding closing character, <code>}</code>, <code>]</code>, or <code>)</code>.

Write a function called <code>is_balanced(string: str) -&gt; bool</code> which verifies the balance of a string.

Example:

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;(())[]{}&#39;) -&gt; True
</code></pre>

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;{([(){}])()}&#39;) -&gt; True
</code></pre>

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;{}[]())&#39;) -&gt; False
</code></pre>

<hr/>

Write a function that tests whether a string of brackets is balanced.

The Brackets Problem

In the context of hypothesis testing, what are type I errors (type one errors) and type II errors (type two errors)? What is the difference between the two?

Bonus: Describe the probability of making each type of error mathematically.

What is the difference between type I and type II errors?

Type I and II Errors

How would you tackle multicollinearity in multiple linear regression?

Multicollinearity in Regression

Let’s say you’re analyzing an AB test that has both a test group and a control group.

<ol>
<li>How do you calculate the sample size necessary for an accurate measurement?</li>

<li>Let’s say that the sample size is similar and sufficient between the two groups. In order to measure very small differences between the two, should the power get bigger or smaller?</li>
</ol>

A/B Test Power Size

What does the backpropagation algorithm do in the context of neural networks? What is the informal intuition behind the algorithm? What are some drawbacks of the algorithm compared to other optimization methods?

Bonus: Formally derive the backpropagation algorithm and prove that it does what it claims to do.

Backpropagation Explanation

Describe a time when you had to define a long-term vision for a project or team and move it from concept to reality.

Interviews for leadership or senior technical roles look for more than just “finishing a project.” Your answer should specifically address:

<ol>
<li>The “Why”: What data or organizational gap necessitated this vision?</li>
<li>The Framework: How did you translate a high-level goal into a roadmap?</li>
<li>The Friction: How did you handle stakeholders or team members who were skeptical of the new direction?</li>
</ol>

Vision Setting and Execution Strategy

Given a <code>employees</code> and <code>departments</code> table, select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary.

Example:

Input:

<code>employees</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>first_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>last_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>department_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>departments</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>percentage_over_100k</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>department_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>number_of_employees</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Let’s you’re tasked with pitching a new feature for Google Home. Your co-worker comes to you with an idea to build a game feature for Google Home.

How would you go about deciding whether Google should build it?

Challenge

Turo Salaries by Position

<div><h2>Senior Product Manager, Marketing Technology</h2>At Turo, we are reinventing rental to unlock independence for all, and growth depends on marketing systems that are fast, reliable, and trusted. We are looking for a Senior Product Manager, Marketing Technology to own the roadmap and strategic direction for Turo's marketing technology platforms and data foundations.This is a high-impact role for a product leader who thrives in complexity, brings structure to ambiguity, and is comfortable owning systems that directly influence revenue across the full acquisition and lifecycle funnel. You will partner closely with Marketing, Engineering, Analytics, and Data Science to modernize our MarTech stack, improve data quality, and help our marketing teams move faster with confidence. This role requires strong technical aptitude, process design skills, and the ability to facilitate alignment across stakeholders with different interests.This role is posted at the Senior Product Manager level but we may consider leveling the role at a broader scope for candidates with exceptional experience leading complex, high-impact platform or data products.<h3>What You Will Do</h3><ol><li>Own the product roadmap and strategic direction for Turo's marketing technology stack across platform engineering, data engineering, and analytics, supporting all channels, including CRM, SEO, SEM, Affiliates, Social, etc.</li><li>Partner cross-functionally with Marketing, Engineering, Data, and Analytics to align priorities and deliver scalable Martech solutions.</li><li>Lead platform-level performance and reliability improvements, including event tracking, system integrations, and landing page performance.</li><li>Translate business needs into data requirements and partner with Data teams on pipelines, schemas, and data quality.</li><li>Define success metrics and measurement frameworks for Martech initiatives, including post-click funnel analysis and optimization.</li><li>Own the landing page and CMS platform, driving improvements to performance, experimentation, and scalability.</li><li>Establish standards, documentation, and best practices across Martech systems to enable consistent execution.</li></ol><h3>Your Profile</h3><ul><li>4+ years of product management experience, ideally including 2+ years in Martech, marketing operations, data platforms, or technical product management.</li><li>Strong process orientation with the ability to bring structure to ambiguity and move teams from reactive execution to roadmap-driven planning.</li><li>Solid technical foundation, including the ability to query data warehouses (SQL) and a working understanding of data pipelines, APIs, and backend systems.</li><li>Familiarity with web and platform performance optimization, including page speed metrics and tracking efficiency.</li><li>Strong stakeholder management skills, with experience aligning teams with competing priorities through clear communication and influence.</li></ul>For this role, the target base salary range in San Francisco is $150,000-$188,000 annually. This role is also eligible for equity and the benefits described below. In general, our ranges reflect the market-based target for new hire salaries based on the level and location of the role. Within the range, individual pay is determined by objective factors assessed during the application and interview process, such as job-related skills, experience, and relevant education or training. We encourage you to talk with your recruiter to learn more about the total compensation and benefits available for this role.Turo highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule Turists will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Your recruiter can share more information about the various in-office perks Turo offers.<h3>Benefits</h3><ul><li>Competitive salary, equity, benefits, and perks for all full-time employees</li><li>Employer-paid medical, dental, and vision insurance (Country specific)</li><li>Retirement employer match</li><li>Learning & Development stipend to invest in your professional development</li><li>Turo host matching program</li><li>Turo travel credit</li><li>Cell phone and internet stipend</li><li>Paid time off to relax and recharge</li><li>Paid holidays, volunteer time off, and parental leave</li><li>For those who are in the office full-time or hybrid we have in-office lunch, office snacks, and fun activities</li></ul>We are committed to building a diverse team. If you are from a background that's underrepresented in tech, we'd love to meet you. Aside from an award winning work environment and the opportunity to be part of the world's largest car sharing marketplace, we are also growing the team quickly - join us! Even if you don't meet every qualification, we are looking for people with enthusiasm for what we do and we will consider you for this and other possibilities.<h3>About Turo</h3>Turo is the world's largest car sharing marketplace where you can book the perfect car for wherever you're going from a vibrant community of trusted hosts across the US, UK, Canada, Australia, and France. Whether you're flying in from afar or looking for a car down the street, searching for a rugged truck or something smooth and swanky, Turo puts you in the driver's seat of an extraordinary selection of cars shared by local hosts.Turo is an Equal Opportunity Employer and a participant in the U.S. Federal E-Verify program. Women, minorities, individuals with disabilities and protected veterans are encouraged to apply. We welcome people of different backgrounds, experiences, abilities and perspectives.Turo will consider qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chance Ordinance, as applicable.We welcome candidates with physical, mental, and/or neurological disabilities. If you require assistance applying for an open position, or need accommodation during the recruiting process due to a disability, please submit a request to People Operations by emailing PeopleOps@turo.com.</div>

Calculate Moving Average	SQL	Easy
Predict Customer Churn	Machine Learning	Medium
A/B Test Significance	Statistics	Medium
Optimize Query Performance	SQL	Hard
Feature Importance Analysis	Machine Learning	Medium
Clean Missing Data	Python	Easy
Neural Network Architecture	Deep Learning	Hard
Calculate Cohort Retention	SQL	Medium
Bayesian Probability	Statistics	Easy
Recommend Similar Products	Machine Learning	Hard

Turo Interview Questions

Turo Interview Guides